Managing a business or an organization in a manner that creates long term value is a complex activity. Further, every business or organization has limited resources and the need for business to accurately monitor their costs and justify resource allocation to achieve specified outcomes in a future calendar time period (e.g., financial quarters) is becoming increasingly important. Unfortunately, the task of organizing business information to determine proper resource allocation is often extensive and troublesome to organize and it is often difficult or impossible for business managers to use this information to make proper decisions. Accordingly, businesses and other organizations typically either overspend their resources or do not avail themselves of statistical data and analysis that can be used to optimize their resource expenditures. For example, business establishments that serve a large number of customers generally have a problem analyzing their transactional information to develop trends in defined population over time. Such trends are desirable to effectively target and determine the effectiveness of various programs for the purposes of optimizing resource allocation to achieve specified outcomes over designed time periods. Further, while it may be known that certain cost reduction programs are hypothesized to be effective to reduce future costs, a need exists for an effective and scientific method and system for optimizing resource allocation that can be shown to achieve specified outcomes over time to maximize a business's investment.
Until now, most economic business models have relied on “calendar time” in determining resource allocation rather than using “experience time” where time is based on the start of an event and its duration (such as the day one purchased a car or the date/time an individual was bitten by a malarial infected mosquito, starting the individual on a “natural” course of fluctuating fevers). Thus, the experience of a population in any calendar time period will vary depending on when each individual “started” in this population. Accordingly, a business organization will be better able to analyze and evaluate the resources that will be necessary to achieve a specific outcome by first understanding this “Cohort Time” heterogeneity of any population during any calendar (or clock) time period.
By way of illustration, manufactures, such as automobile manufactures, are actively searching for ways to reduce the probability of realizing extensive repair costs under warranty. Despite dramatic improvement in new-vehicle quality at most major automobile manufacturers over the past decade, the reduction of warranty cost is a large area for potential cost reductions. While manufactures have developed sophisticated statistical tracking systems, until now there was no adequate method or system to assess available resources today to reduce specified outcomes (i.e., warranty costs) in the future.
Recently, the optimization of resource allocation has become particularly important for businesses engaged in the health care industry. Due to significant increases in health care costs, health care providers and service management organizations have become under increased pressure by customers to find ways of lowering or at least slow the rate of growth of health care costs. As a result of such pressure, health care providers have implemented numerous population-based programs, such as wellness programs, disease management programs, and other health-inducing and cost-reduction programs, designed to improve the overall health of the population thereby reducing, at least theoretically, overall health care costs. Such health care organizations, however, are in need of a system that can qualitatively analyze program performance in order to optimize allocation of health care services and expenditures over time to achieve specified outcomes.
Accordingly, a need exist for a method and system to qualitatively analyze cost reduction programs and for analyzing information for allocating resources to best serve a business' goals. In health care and product warranty work, the ventral issues are the same. An “individual unit” with a certain characteristic that makes it eligible for inclusion in a defined population, is entered into the population at a certain “start time” (clock or calendar time) and remains “eligible” for this population during a known and quantifiable duration of time. Furthermore, this population has a greater than zero probability of experiencing some event at a future time period, an event with some economic value attached to it. This event, the “individual unit,” the date of the event, and the “cash value” of such event is captured by a transaction system. The method and apparatus transforms this information into usable estimates for resource allocation decisions needed to achieve specified outcomes.